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Proceedings Paper

An efficient stereo matching based on superpixel segmentation
Author(s): Haichao Li; Ke Han
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Paper Abstract

The traditional semi-global matching methods provide a good trade-off between accuracy and complexity compared with the local matching methods and global matching methods, however, they still need to traverse the full disparity search range to find the best matching point. Therefore, it still needs high computational cost especially for stereo images with large disparity search range. We proposes an efficient semi-global matching method that disparity search range is reduced based on 3D plane fitting. Firstly, the simple linear iterative clustering (SLIC) algorithm is adopted to segment the stereo images. Secondly, the dense SIFT keypoints are extracted and matched from the left and right images. Thirdly, similar adjacent superpixels are merged based on the gray mean and variance, and for each merged region, 3-D plane is fitted based on matched keypoints. Finally, the pixel-wise disparity search range is limited into several pixels for more-global matching method which can reduce the computational complexity and obtain an accurate disparity map. Experimental results demonstrate that the computational speed of the new semi-global matching method is several times faster than that of the original method, as well as offering a more accurate disparity map.

Paper Details

Date Published: 18 November 2019
PDF: 7 pages
Proc. SPIE 11187, Optoelectronic Imaging and Multimedia Technology VI, 111870B (18 November 2019); doi: 10.1117/12.2537259
Show Author Affiliations
Haichao Li, Qian Xuesen Lab. of Space Technology (China)
Ke Han, Beijing Univ. of Posts and Telecommunications (China)

Published in SPIE Proceedings Vol. 11187:
Optoelectronic Imaging and Multimedia Technology VI
Qionghai Dai; Tsutomu Shimura; Zhenrong Zheng, Editor(s)

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